Visual field (VF) testing is a noninvasive technique for the detection of a wide range of visual system disorders. VF testing is also used for assessing the progression of various degenerative diseases such as glaucoma. Unfortunately, the interpretation of VF test data involves the analysis of a large amount of data and in many cases may be difficult even for a skilled practitioner. VF data shows large variances even for normal eyes, which further complicates analysis. In Phase 1, ORINCON will design and implement a novel neural network-based software package to automate the interpretation of VF test data for the detection of glaucoma. The software will classify VF test data into nonrial, glaucoma suspect, glaucomatous, and unknown (novel-none of the above). The software will also extract and present a set of simple rules used to produce the classification. The computational architecture will enable inclusion of ancillary and other diagnostic data in the analysis. In Phase 11, ORINCON will implement a complete, user-friendly analysis software that will, with minimum intervention by the operator, classify VF test data into a variety of visual field defects and provide the reasoning behind these classifications. PROPOSED COMMERCIAL APPLICATION:NOT AVAILABLE